How AI in the workplace will affect collaboration and job performance
AI in the workplace can enhance unified communications and collaboration services. But IT decision-makers must consider three effects on employee collaboration and job roles.
AI is at the forefront of the broader digital transformation story for many organizations. But the digital transformation process will unfold over many years. Many tools and business processes are still rooted in analog ways, so we have a long way to go before we're living in an all-digital world.
AI brings great promise to the emerging digital workplace, and IT decision-makers should consider how AI might transform workplace communication and collaboration. To some extent, AI in the workplace is already here. But, in terms of the future of work, three implications for employee collaboration must be considered.
The effect on jobs
The business value for AI in the workplace will primarily be in automation. On the collaboration front, this means applying AI to handle routine or low-level tasks that impede real productivity.
We're already seeing this transformation with digital assistants, such as smart speakers, like Alexa for Business, which can help organize and manage meetings. While these tasks are rather basic, the applications will get smarter over time, and workers can entrust them with more complex tasks.
As AI could free up workers from mundane tasks, management will view this as a driver for higher productivity. Inevitably, this new workflow will mean greater expectations for worker output, such as completing projects faster, managing bigger teams and handling more projects.
As automation plays a bigger role in the workplace, workers will be expected to perform in a more automated fashion, which might affect employee morale. AI will certainly introduce better ways to collaborate, but most jobs will become harder, not easier.
The effect on successful skills
The above scenario has pros and cons, but workers can still thrive if they have the right skills. AI-driven collaboration will create new responsibilities and expectations for workers, and IT decision-makers need to understand what new skills will be needed.
On a basic level, as the workplace becomes more collaborative, employees will need strong project management skills. Workers who regularly manage teams will already have that skill set, but it will become a more core skill for knowledge workers.
AI in the workplace also means data -- more data and new data. Tomorrow's collaboration applications will generate an endless stream of data that workers will have to manage.
While AI-based analytics tools have started to emerge in unified communications services, they have not become mainstream for all levels of workers. In time, analytics skills will become central for assessing collaboration processes and outcomes, especially for how AI is enabling better results.
The effect on performance evaluation
The same metrics used by workers to manage collaboration will also be used to evaluate their own performance. A key aspect of digital transformation will entail digitizing all facets of communication. When driven by AI, this communications shift should create better collaboration efficiency, but that also means metrics tied to every touchpoint and interaction.
In this environment, the digital trail for each worker will become especially granular, and new performance metrics will emerge. These metrics will measure the quality and business value of collaboration outcomes, as well as the quality of employee performance.
AI-driven applications will become pervasive enough that workers, for example, will no longer be able to catch up on email and social media during a web conference with their team. AI-based metrics will track engagement for each team member, and chatbots will provide prompts when workers aren't staying the course.
This may not present a pretty picture for privacy and workplace satisfaction, but AI cuts both ways. Employers will need to strike a balance for evaluating employee performance. All businesses want the benefits that come from AI-driven automation, but the human side of work must be nurtured as well. Otherwise, collaboration outcomes will only improve on paper but not in spirit.